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# -*- coding: utf-8 -*-
"""
school_api.check_code.predict
~~~~~~~~~~~~~~~~
This module provides functions for Identification verification code
:copyright: (c) 2018 by dairoot.
:license: MIT, see LICENSE for more details.
"""
import os
from io import BytesIO
import numpy as np
from PIL import Image
class CheckCode(object):
""" 正方系统验证码识别 """
data_file = os.path.dirname(os.path.realpath(__file__)) + '/theta.dat'
real_all_theta = np.matrix(np.loadtxt(data_file)).transpose()
def __init__(self):
self.img = None
def photo_to_text(self):
'''
图片转数据
'''
x_size, y_size = self.img.size
y_size -= 5
piece = (x_size - 22) // 8
centers = [4 + piece * (2 * i + 1) for i in range(4)]
photo_data = []
for center in centers:
single_img = self.img.crop((center - (piece + 2), 1, center + (piece + 2), y_size))
width, height = single_img.size
photo_data_x = []
for h_index in range(0, height):
for w_index in range(0, width):
pixel = single_img.getpixel((w_index, h_index))
photo_data_x.append(int(pixel == 255))
photo_data.append(photo_data_x)
return photo_data
def verify(self, img_stream):
'''
将图片转成numpy数组数据 与 训练好的模型 进行匹配
'''
obj = BytesIO(img_stream)
img = Image.open(obj).convert("L")
self.img = self.denoise_img(img)
data = np.matrix(self.photo_to_text())
data = np.hstack((np.ones((data.shape[0], 1)), data))
all_predict = 1.0 / (1.0 + np.exp(-(np.dot(data, self.real_all_theta))))
pred = np.argmax(all_predict, axis=1)
answers = map(chr, map(lambda x: x + 48 if x <= 9 else x + 87, pred))
return ''.join(answers)
@staticmethod
def denoise_img(img):
'''图片降噪处理'''
img2 = Image.new("L", img.size, 255)
for x in range(img.size[1]):
for y in range(img.size[0]):
pix = img.getpixel((y, x))
if pix == 17: # these are the numbers to get
img2.putpixel((y, x), 0)
return img2
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